Abstract

This is the first chapter in Part 3. Its purpose is to contrast the value structure of platform systems with step processes from a technological perspective. I first review the basic technical architecture of computers and argue that every computer is inherently a platform for performing computations as dictated by their programs. I state and prove five propositions about platform systems, which stand in contrast to the propositions derived for step processes in Chapter 8. The propositions suggest that platform systems and step processes call for different forms of organization. Specifically, step processes reward technical integration, unified governance, risk aversion, and the use of direct authority, while platform systems reward modularity, distributed governance, risk taking, and autonomous decision-making. Despite these differences, treating platform systems and step processes as mutually exclusive architectures sets up a false dichotomy. Creating any good requires carrying out a technical recipe, i.e., performing a series of steps. Step processes in turn can be modularized (at the cost of lower efficiency) by creating buffers between steps. I show that the optimal number of modules (and buffers) increases as the underlying rate of technical change goes up. When the underlying technologies are changing rapidly, it makes sense to sacrifice some degree of flow efficiency for options to mix-and-match modular components.

More from the Author

The IBM PC was the first digital computer platform that was open by as a matter of strategy, not necessity. The purpose of this chapter is to understand the IBM PC as a technical system and set of organization choices in light of the theory of how technology shapes organizations. In Chapter 7, I argued that sponsors of large technical systems (including platform systems) must manage the modular structure of the system and property rights in a way that solves four inter-related problems: provide all essential functional components, solve system-wide technical bottlenecks wherever they emerge, control and protect one or more strategic bottleneck, and prevent others from gaining control of any system-wide strategic bottleneck. I use this framework to understand how IBM initially succeeded with the PC platform and then lost its position as platform sponsor in the industry it had created.

The purpose of this chapter is to present analytic tools based on functional maps that can be used to identify investment opportunities and to formulate strategy in large, evolving technical systems. I argue that the points of value creation and value capture in a technical system are the system’s bottlenecks. Bottlenecks arise first as important technical problems to be solved. Once the problem is solved, the solution in combination module boundaries and property rights can be used to capture a stream of rents. In this chapter I extend the functional mapping techniques developed in the last chapter to locate technical and strategic bottlenecks, modules, and property rights. I then show how these analytic tools can be used to construct narratives explaining the dynamics of three nascent technical systems: early aircraft, high-speed steel in machine tools, and container shipping.

The purpose of this chapter is to relate the theory of task networks and technology set forth in previous chapters to theories of firm boundaries from economics and management. Complementary goods have more value when used together than separately. Complementarity may be strong or weak. Strong complements are specific and unique goods that have no value (or greatly diminished value) unless all are present in use. In the task network, dense technical interdependencies create strong complementarity, but it can arise for other reasons as well.
Transaction cost economics and property rights theory advise that strong complements should be placed under unified governance, for example, through common ownership. Agency theory suggests that weak complementarity can be handled via arms-length transactions and contracts. Furthermore, strong or weak complementarity are not innate properties of tasks and assets but can be the result of choices regarding task networks, incentives, and job design.
Supermodular complementarity exists when more of one input makes more of another input more valuable. Distributed supermodular complementarity (DSMC) exists when two or more independent actors can create complementary value by pursuing their own interests and will not find it advantageous to combine in order to coordinate their actions. I derive formal conditions under which DSMC holds as a consistent pattern in a dynamic equilibrium. Given DSMC, clusters of firms making different complementary goods, including open platforms with surrounding ecosystems, can survive and compete effectively against integrated firms that control all complementary inputs.